Why Numpy ?
NumPy revolutionized the way we handle numerical data in Python. It is created to address the limitations of traditional Python lists when it comes to numerical computing. It is developed by Travis Olliphant in 2005.
NumPy provides a powerful array object that is both efficient and flexible. Its primary goal is to facilitate complex mathematical and scientific operations by introducing array-oriented computing capabilities. NumPy’s design allows for seamless integration with other scientific libraries, enabling faster execution of numerical tasks.
As a result, NumPy has become a cornerstone in the Python ecosystem, essential for data manipulation, machine learning, and scientific research.
Installation of Numpy Using PIP
Open your command prompt or terminal and run the following command:
pip install numpy
NumPy Tutorial – Python Library
NumPy is a general-purpose array-processing Python library which provides handy methods/functions for working n-dimensional arrays. NumPy is a short form for “Numerical Python“. It provides various computing tools such as comprehensive mathematical functions, and linear algebra routines.
- NumPy provides both the flexibility of Python and the speed of well-optimized compiled C code.
- Its easy-to-use syntax makes it highly accessible and productive for programmers from any background.
This NumPy tutorial helps you learn the fundamentals of NumPy from Basics to Advanced, like operations on NumPy array, creating and plotting random data sets, and working with NumPy functions.